Low relative skeletal muscle mass (SMM) or sarcopenia significantly contributes to the decline in physical functioning among the elderly. Very little is known about genetic risk factors and their interactions with environmental factors in aging-related SMM loss. There are some indications that inflammatory factors and reduced levels of anabolic hormones are associated with lower muscle mass. These associations need to be confirmed in larger prospective studies and the exact role of each identified biomarker in the development of sarcopenia remains to be investigated. Since physical function impairment and disability are more prevalent in women than in men during later life, it is especially important to understand the mechanisms of muscle loss and to prevent sarcopenia among older women. The primary objective of this study is to identify genetic factors and biomarkers that are relevant to low SMM and high rates of SMM loss in older women. We will achieve two specific aims: 1) assess the association of cytokines and hormonal factors with low SMM and the rate of SMM loss;and 2) evaluate the role of genetic variation in catabolic inflammatory cytokines (IL-6, IL-1, TNF-alpha) as well as in anabolic growth factors (IGF1, Growth Hormone) related to SMM and the rate of SMM loss in a large cohort of Hispanic and non-Hispanic White postmenopausal women. Study participants will come from the Women's Health Initiative Observational Study. All of these women have had repeat body composition measurements by using Dual-energy X-ray Absorptiometry (DXA) during the nine- year follow-up. Their SMM will be assessed using a DXA-derived method developed by this research team. Genetic variations in selected catabolic (e.g.IL-1, IL6, TNF-a) as well as anabolic (e.g. IGF-1, and GH) factors will be assessed for the entire sample (n = 2800). Analyses of biomarkers, including IL-6, TNF-a, adiponectin, C-reactive protein, IL-1ra, IL-6sR, TNF Rll, acid labile subunitJGF-1, and IGFBP-3, will be conducted among 50 percent of the participants in this study. Regression and mixed effects models will be used in the final data analysis. This study is unique and innovative in the study design, selection of bioassays, and the study population. Results of this study will have significant impacts on the prevention and reduction of adverse health outcomes associated with sarcopenia of older women in the United States.